9 citations · 22 across the 5 of their papers we have counts for
6 papers
Exploring the Application of Large-scale Pre-trained Models on Adverse Weather Removal
Zhentao Tan, Yue Wu, Qiankun Liu +4
Image restoration under adverse weather conditions (e.g., rain, snow and haze) is a fundamental computer vision problem and has important indications for various downstream applica…
UIA-ViT: Unsupervised Inconsistency-Aware Method based on Vision Transformer for Face Forgery Detection
Wanyi Zhuang, Qi Chu, Zhentao Tan +5
Intra-frame inconsistency has been proved to be effective for the generalization of face forgery detection. However, learning to focus on these inconsistency requires extra pixel-l…
Reduce Information Loss in Transformers for Pluralistic Image Inpainting
Qiankun Liu, Zhentao Tan, Dongdong Chen +6
Transformers have achieved great success in pluralistic image inpainting recently. However, we find existing transformer based solutions regard each pixel as a token, thus suffer f…
Real-time Online Multi-Object Tracking in Compressed Domain
Qiankun Liu, Bin Liu, Yue Wu +2
Recent online Multi-Object Tracking (MOT) methods have achieved desirable tracking performance. However, the tracking speed of most existing methods is rather slow. Inspired from t…
Online Multi-Object Tracking with Unsupervised Re-Identification Learning and Occlusion Estimation
Qiankun Liu, Dongdong Chen, Qi Chu +4
Occlusion between different objects is a typical challenge in Multi-Object Tracking (MOT), which often leads to inferior tracking results due to the missing detected objects. The c…
Joint Face Image Restoration and Frontalization for Recognition
Xiaoguang Tu, Jian Zhao, Qiankun Liu +5
In real-world scenarios, many factors may harm face recognition performance, e.g., large pose, bad illumination,low resolution, blur and noise. To address these challenges, previou…